CcNav : Understanding Compiler Optimizations in Binary Code
Program developers spend significant time on optimizing and tuning programs. During this iterative process, they apply optimizations, analyze the resulting code, and modify the compilation until they are satisfied. Understanding what the compiler did with the code is crucial to this process but is very time-consuming and labor-intensive. Users need to navigate through thousands of lines of binary code and correlate it to source code concepts to understand the results of the compilation and to identify optimizations. We present a design study in collaboration with program developers and performance analysts. Our collaborators work with various artifacts related to the program such as binary code, source code, control flow graphs, and call graphs. Through interviews, feedback, and pair-analytics sessions, we analyzed their tasks and workflow. Based on this task analysis and through a human-centric design process, we designed a visual analytics system Compilation Navigator (CcNav) to aid exploration of the effects of compiler optimizations on the program. CcNav provides a streamlined workflow and a unified context that integrates disparate artifacts. CcNav supports consistent interactions across all the artifacts making it easy to correlate binary code with source code concepts. CcNav enables users to navigate and filter large binary code to identify and summarize optimizations such as inlining, vectorization, loop unrolling, and code hoisting. We evaluate CcNav through guided sessions and semi-structured interviews. We reflect on our design process, particularly the immersive elements, and on the transferability of design studies through our experience with a previous design study on program analysis.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:27 |
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| Enthalten in: |
IEEE transactions on visualization and computer graphics - 27(2021), 2 vom: 13. Feb., Seite 667-677 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Devkota, Sabin [VerfasserIn] |
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| Links: |
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| Themen: |
Journal Article |
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| Anmerkungen: |
Date Completed 30.09.2021 Date Revised 30.09.2021 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1109/TVCG.2020.3030357 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Program developers spend significant time on optimizing and tuning programs. During this iterative process, they apply optimizations, analyze the resulting code, and modify the compilation until they are satisfied. Understanding what the compiler did with the code is crucial to this process but is very time-consuming and labor-intensive. Users need to navigate through thousands of lines of binary code and correlate it to source code concepts to understand the results of the compilation and to identify optimizations. We present a design study in collaboration with program developers and performance analysts. Our collaborators work with various artifacts related to the program such as binary code, source code, control flow graphs, and call graphs. Through interviews, feedback, and pair-analytics sessions, we analyzed their tasks and workflow. Based on this task analysis and through a human-centric design process, we designed a visual analytics system Compilation Navigator (CcNav) to aid exploration of the effects of compiler optimizations on the program. CcNav provides a streamlined workflow and a unified context that integrates disparate artifacts. CcNav supports consistent interactions across all the artifacts making it easy to correlate binary code with source code concepts. CcNav enables users to navigate and filter large binary code to identify and summarize optimizations such as inlining, vectorization, loop unrolling, and code hoisting. We evaluate CcNav through guided sessions and semi-structured interviews. We reflect on our design process, particularly the immersive elements, and on the transferability of design studies through our experience with a previous design study on program analysis | ||
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| 700 | 1 | |a Kunen, Adam |e verfasserin |4 aut | |
| 700 | 1 | |a Legendre, Matthew |e verfasserin |4 aut | |
| 700 | 1 | |a Isaacs, Katherine E |e verfasserin |4 aut | |
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